Sign Language Translator

A machine vision and deep learning-based solution for translating sign language gestures into text or speech. This project aims to bridge the communication gap between individuals who use sign language and those who do not.

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🚀 Features

• Image Collection: Automatically captures and collects images required for gesture recognition.
• Dataset Creation: Prepares a comprehensive dataset for training.
• Model Training: Includes a script to train a classifier for recognizing sign language gestures.
• Inference: Real-time or pre-recorded gesture translation into text/speech.
• User-Friendly: Easily extendable and adaptable to other sign languages or datasets.

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🛠️ Technologies Used

• Programming Language: Python
• Libraries and Tools:
  • OpenCV for real-time image processing
  • TensorFlow/Keras or PyTorch for training the classifier
  • Numpy, Pandas - for data processing.

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📁 Project Structure

├── scripts/                     # All scripts related to main functionalities
│   ├── imageCollection.py       # Script to collect sign language images
│   ├── createDataset.py         # Script to preprocess and organize datasets
│   ├── trainClassifier.py       # Script for training the model
│   ├── inferenceClassifier.py   # Script for running predictions
│
├── README.md                    # Project documentation (this file)
├── .gitignore                   # List of ignored files and directories

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🧩 Prerequisites

Before running the application, make sure to install the following:

1. Python 3.8 or higher - Download Python.
2. Install the required dependencies:

   pip install -r requirements.txt

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⚙️ Installation

1. Clone the repository:

   git clone <repository-url>
   cd Sign-Language-Translator

2. Set up a Python virtual environment:

   python -m venv .venv
   source .venv/bin/activate   # On macOS or Linux
   .venv\Scripts\activate      # On Windows

3. Install dependencies:

   pip install -r requirements.txt

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▶️ Usage

1. Run Image Collection Script: Collect hand gesture images to create a dataset:

   python scripts/imageCollection.py

2. Create Dataset: Process the collected images into labeled datasets.

   python scripts/createDataset.py

3. Train the Classifier: Train a machine learning model to recognize gestures.

   python scripts/trainClassifier.py

4. Run Inference: Translate sign language into text or speech using the trained model.

   python scripts/inferenceClassifier.py

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🤝 Contributing

Contributions are welcome! Please follow these steps to contribute:

1. Fork the repository.
2. Create a new feature branch:

   git checkout -b feature-name

3. Commit changes:

   git commit -m "Add your message"

4. Push to the branch:

   git push origin feature-name

5. Submit a pull request.

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📜 License

This project is licensed under the MIT License.

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🌟 Acknowledgements

Special thanks to the developers of libraries like TensorFlow, OpenCV, and others that made this project possible.